Raised in Birkenhead, across the Mersey River from Liverpool, England, Wilmott began turning his interests into businesses at an early age. When he was in a childhood pet-keeping phase, he started a zoo on his porch and in his garden—with mice, guinea pigs, goldfish, and a tortoise—and charged admission for entry. Later, he paid for his education by juggling; his hands are still covered with tiny scars from tossing around burning torches.

Although neither of his parents went to college, Wilmott made it to Oxford, where he earned a D.Phil. (Oxford’s equivalent of a Ph.D.) in applied mathematics in 1985. When he wasn’t competing against Cambridge on the ballroom-dancing team, he worked on modeling phenomena like the flow of air over a propeller blade or water around the hull of a submarine. He was introduced to financial mathematics a few years after he got his doctorate, when a colleague inherited some options. “It had never occurred to me that there was room for the kind of math I did in finance,” Wilmott says. “I thought the financial world was all pinstripes and connections and cigars.”

Wilmott began lecturing and writing about math and finance and started consulting; he did research for Japan’s Nomura Holdings one day a week for six years. Along the way, his skepticism about the field grew. “When I started, I tended to believe everything I read,” he says. “The books would say that volatility is constant, and I would say, ‘Okay. Fair enough.’ ” Volatility measures divergence from the mean, and at the heart of many formulas for finding out how much a financial product is worth is an assumption that volatility, though it may stray a bit, always returns to a normal level. “But as I started looking at more and more data,” he continues, “I began to realize that volatility is not constant.” Large deviations—the black swans that Taleb made famous in his book—were to be expected. “Finance isn’t like fluid dynamics,” Wilmott says. “You’re modeling human behavior, so you’re never going to get it right.”

From 2002 to 2005, Wilmott was a partner at Caissa Capital, a hedge fund that had as much as $170 million under management and speculated on changes in market volatility by buying and selling options on Standard & Poor’s 500-stock index. Caissa’s main fund averaged a 9.4 percent annual return. It closed down following a partner disagreement. Wilmott now oversees a global distance-learning program called the Certificate in Quantitative Finance, which trains bankers in the intricacies of the craft. The program, run from a slick office amid the skyscrapers of downtown London, has students from most major banks and turns out about 500 graduates a year.

There are two kinds of articles in Wilmott: the ones you can read and the ones you can’t. Examples of the first include “What Is the Interest Rate in Hell?” by Aaron Brown, which dissects financial scenarios in the work of thriller writer Jim Thompson, and “Quant Life in Singapore” by Manoj Thulasidas, musings on the Asian country’s respect for its small cadre of quants. Espen Haug, a regular Wilmott contributor, occasionally adds a quant comic strip in which a superhero in dark sunglasses travels the globe battling mathematically impossible phenomena like “negative volatility.” And there are car reviews. When Wilmott’s not quanting, he’s usually thinking about cars. He has an Alfa Romeo and a Jensen that he loves so much, he rarely drives it.

The other type of articles are dubbed “technical papers.” For quants, these are the heart of the magazine and its value, and they traffic in the kind of brain-melting math that separates the casual reader from the professional insider. The November 2007 issue, for example, includes a 22-page piece, the title of which alone is scary: “Analytical Techniques for Synthetic C.D.O.’s and Credit Default Risk Measures in Static Fac­tor Models.” It discusses complex mathematical equations.

Much as he loves the hard math, if Wilmott had his way, quantitative finance would better balance its academically quantitative aspect with its market-based financial one. “You have traders and you have quants, and very rarely do you have someone who sees both sides,” says Wilmott, who considers this disconnect to be the root of the current crisis. The quants were using their models to value products that they had no experience trading, and the traders were dealing with products they could never properly value themselves.

“Banks and hedge funds employ mathematicians with no financial-market experience to build models that no one is testing scientifically for use in situations where they were not intended by traders who don’t understand them,” Wilmott wrote in a recent post on his blog. “And people are surprised by the losses!”

Not too long ago, Wilmott wandered into an auction at the Savoy, the famous London hotel, and his visit reveals a little of how a quant’s brain works. The Savoy was unloading just about everything, from ashtrays to beds, in anticipation of a $200 million renovation. Fifty beds went up for sale one by one, and in that, Wilmott saw a picture of a market in miniature. He charted each of the selling prices, which spiked and dropped wildly over time, though all the beds sold were apparently identical. For him, it exemplified the challenge that models face in trying to predict human behavior.

On the way out, Wilmott passed a man happily examining his new purchase. It was Uri Geller, the magician who famously convinced scientists that he could bend spoons using just the power of his mind. Naturally, Geller had purchased a box of silver spoons. “He gave me a spoon-bending demonstration, but it wasn’t very convincing,” Wilmott says, with the troubles of the past months clearly in mind. “It just goes to show you how easy it is to fool a man of science.”